magazine Spring 2001 tinbergen institute 3 Tinbergen Magazine is published by Tinbergen Institute, the Institute for economic research of Erasmus Universiteit Rotterdam, Universteit van Amsterdam and Vrije Universiteit Amsterdam. Economic Dynamics From a linear, perfectly rational view towards bounded rationality, non-linearity and complex adaptive systems Global challenges of capital markets integration Modern economics in action in poor countries An interview with development economist Jan Willem Gunning Economic Dynamics From a linear, perfectly rational view towards bounded rationality, non-linearity and complex adaptive systems Global challenges of capital markets integration Modern economics in action in poor countries An interview with development economist Jan Willem Gunning
Transcript
magazine
Spring 2001
tinbergen institute3
Tinbergen Magazine is published
by Tinbergen Institute, the
Institute for economic research of
Erasmus Universiteit Rotterdam,
Universteit van Amsterdam and
Vrije Universiteit Amsterdam.
Economic Dynamics
From a linear, perfectly rational view towards
bounded rationality, non-linearity and complex
adaptive systems
Global challenges of capital markets integration
Modern economics in action in poor countries
An interview with development economist
Jan Willem Gunning
Economic Dynamics
From a linear, perfectly rational view towards
bounded rationality, non-linearity and complex
adaptive systems
Global challenges of capital markets integration
Modern economics in action in poor countries
An interview with development economist
Jan Willem Gunning
In depth
References
In short
Up close
2
www.tinbergen.nl
In this issue
In depth
Economic Dynamics
From a linear, perfectly rational view towards
bounded rationality, non-linearity and
complex adaptive systems
by Cars H. Hommes
Global challenges of capital markets integration
by Jean-Marie Viaene
Up close
Modern economics in action in poor countries
An interview with development economist
Jan Willem Gunning
by Bert Hof
In short
Discussion papers
Papers in journals
Other publications
Theses
References
Discussion papers and theses that have appeared
in the last half year
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tinbergen institute
magazine
Spring 2001
tinbergen institute3
Tinbergen Magazine is published
by Tinbergen Institute, the
Institute for economic research of
Erasmus Universiteit Rotterdam,
Universteit van Amsterdam and
Vrije Universiteit Amsterdam.
Economic Dynamics
From a linear, perfectly rational view towards
bounded rationality, non-linearity and complex
adaptive systems
Global challenges of capital markets integration
Modern economics in action in poor countries
An interview with development economist
Jan Willem Gunning
Economic Dynamics
From a linear, perfectly rational view towards
bounded rationality, non-linearity and complex
adaptive systems
Global challenges of capital markets integration
Modern economics in action in poor countries
An interview with development economist
Jan Willem Gunning
Highlighting ongoingresearch at TinbergenInstitute for policymakersand scientists.
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tinbergen magazine 3, spring 2001
A linear worldview, according to whichthe economy is an inherently stable system,still seems to dominate the minds of manyeconomists. Such a view of the economydates back to the thirties, when Frisch,Slutsky and Tinbergen convincingly showedthat linear dynamic models buffeted withnoise generated time series patterns verysimilar to observed business cycle fluctua-tions. This linear view was challenged in theforties and fifties by the non-linear businesscycle models of Goodwin, Hicks and Kaldor.The limit cycles generated by these modelswere much too regular, however, to explainthe occasionally highly irregular movementsin economic and financial time series data.Another important problem in these earlynon-linear business cycle models was thatagents were in fact irrational, since theirexpectations were systematically wrongalong the regular business cycles.
These shortcomings stimulated therational expectations revolution – whereagents are assumed to be perfectly rational,and expectations, on average, coincide withrealisations. A representative, perfectly ratio-nal agent fits nicely into a linear view of aglobally stable economy.
In mathematics and physics, thingschanged dramatically in the sixties and theseventies due to the discovery of determinis-tic chaos. The MIT meteorologist EdwardLorenz discovered that a simple non-linearsystem of three differential equations couldgenerate highly irregular and seeminglyunpredictable time series patterns. Even in asimple world described by just a couple ofnon-linear equations, (long-run) predictionbecomes very difficult. In the early seventies,Ruelle and Takens developed a mathematicalproof that a simple non-linear system ofthree or four differential equations, withoutany external random disturbances, canindeed exhibit complicated long-run dynamicbehaviour on a strange attractor. Economistsbecame much inspired by another mathemat-ical article “Period three implies chaos,” by Li and Yorke in 1975, showing that manynon-linear difference equations in one singlevariable exhibit chaos. For example,Benhabib and Day (1982) and Grandmont(1985) built simple non-linear business cyclemodels within the paradigm of rationalexpectations and competitive markets, gener-ating chaotic business cycles.
I n d e p t h
Economic DynamicsFrom a linear, perfectly
rational view towards
bounded rationality,
non-linearity and complex
adaptive systems
By Cars H. Hommes●
●
Cars Hommes is Professor
of Economic Dynamics at the
Department of Economics
at the Universiteit van
Amsterdam. His current
research interests include
expectations and learning,
non-linear dynamics,
complex adaptive systems
and multi-agent financial
modelling. In 1998, he
received a NWO-MaG Pioneer
grant to start a Center for
Nonlinear Dynamics in
Economics and Finance
(CeNDEF).
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tinbergen magazine 3, spring 2001
An early signature of chaosThe roots of the “chaos revolution” in
the sixties and seventies, however, could betraced back to the end of the nineteenth cen-tury in the work of famous French mathe-matician Henri Poincaré. In 1887, King OskarII of Sweden promised to award a prize forthe best essay concerning the question “Isour solar system stable?” In his prize-winningessay, Poincaré showed that the motion in asimple three-body system, consisting of sun,earth and moon, need not be periodic, butmay become highly irregular and unpre-dictable – chaotic, in modern terminology.Poincaré introduced the notion of homoclinicorbit, an intersection point between the sta-ble and the unstable manifold of an equilibri-um steady state. Poincaré’s notion of homo-clinic orbits turned out to be a key feature ofcomplicated motion and strange attractors,and may be seen as an early signature ofchaos.
Evolutionary dynamicsBut what does all this have to do with
economics? In a recent article (Brock andHommes, 1997), a heterogeneous agent “cob-web” hog-cycle model with rational versusnaive producers was studied. Agents couldeither buy rational expectations forecasts atpositive information costs, or freely obtain asimple, naive forecasting rule. Fractions of
the two types change over time according toan evolutionary fitness measure. Agents areboundedly rational in the sense that mostagents will follow the strategy that has per-formed well in the recent past. This simpleevolutionary economic system exhibits com-plicated price fluctuations when the trader’sintensity of choice to switch strategies ishigh. When the economy is close to itssteady state, naive forecasts perform fairlywell, and most agents will therefore use thecheap naive forecast. This will drive pricesaway from the steady state and destabilisethe economy. But when prices diverge fromthe steady state, forecasting errors fromnaive expectations will increase; at somepoint it will become more profitable toswitch and to buy the rational forecast. Theeconomy will stabilise, and prices will moveback closer to the steady state (and the storyrepeats). This simple evolutionary economic
interaction between a “close to the steadystate destabilising force,” and a “far from thesteady state stabilising force,” is closelyrelated to Poincaré’s classical notion of ahomoclinic orbit; as such, it may be seen asa signature of potential instability and chaosin an evolutionary system with boundedlyrational agents.
Financial markets as complexadaptive systemsIn another recent article (Brock and
Hommes, 1998), the evolutionary set-up wasapplied to a standard asset-pricing model.Agents can invest in either a risk-free asset,such as a bond, which pays a fixed returneach period, or in a risky asset, such as astock, which pays an uncertain dividend. Intheir investment decision, agents use differ-ent forecasting strategies to predict futureprices and dividends. For example, funda-mentalists use forecasts based upon marketfundamentals such as dividends and interestrates. In contrast, technical traders look forpatterns in past prices and use simple trend-following forecasting rules. Again, the evolu-tionary dynamics exhibits rational routes torandomness, that is, bifurcation routes tocomplicated asset price movements as theintensity of choice to switch forecastingstrategies increases.
This simple evolutionary economic interaction
may be seen as a signature of potential instability
and chaos in an evolutionary system with boundedly
rational agents.
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tinbergen magazine 3, spring 2001
Figure 1 illustrates the fractal structure ofone of the strange attractors in the asset-pricing model with evolutionary learning.The fundamental RE price of the risky asset,as given by the discounted sum of expectedfuture dividends, corresponds to the originin figure 1. Asset prices jump irregularlyover the strange attractors, and may deviatefrom the fundamental price. The fractalstructure of the strange attractor around theunstable fundamental steady state is illus-trated in the right-hand panel of figure 1.Asset price fluctuations are characterised bytemporary bubbles, triggered by news abouteconomic fundamentals, which may be rein-forced by speculative trend-following trad-ing. A similar mechanism may, for example,be responsible for the strong decline of morethan 50% of the NASDAQ index in the past 12months, which was triggered by bad newsabout expected earnings of new-economyfirms and reinforced by “market psychology”and investors’ pessimism.
Rationality versus boundedrationalityA good feature of rationality is that
“there are only a few ways one can be right.”The rational expectations approach thus putsa natural discipline on agents’ forecastingrules and minimises the number of freeparameters. In contrast, under boundedrationality, “there are many ways one can bewrong,” and it is not clear at all how tomodel deviations from rationality.
The philosophy underlying our evolutionaryapproach is to use simple forecasting rulesand “let evolution decide who is right.”Forecasting rules that perform poorly will, attimes, be driven out of the market, but mayenter again in periods where they performwell. Such an adaptive equilibrium fits intowhat Sargent calls an equilibrium theory ofmisspecification. Realised market prices andexpectations about these prices co-evolveover time. Sometimes this may lead to a fair-ly stable outcome, with prices movingtowards the fundamental steady state of theeconomy. At other times, trend-followingmay lead to an unstable outcome – possiblywith chaotic asset-price fluctuations.
Stylised factsHow realistic are the asset-price fluctua-
tions in our simple adaptive systems?Important stylised facts observed in manyreal financial time series include unpre-
dictability of returns, clustered volatility andlong memory. Figure 2 illustrates thesestylised facts for 40 years of daily S&P 500returns. The S&P 500 returns plot clearlyshows that large (small) price changes tendto be followed by large (small) price changes.The small magnitudes of the sample autocor-relations of returns show that, from a linearviewpoint, the S&P 500 returns are unpre-dictable. In contrast, the sample autocorrela-tions of squared returns and absolute returns
-0.8
-0.4
0
0.4
0.8
-0.8 -0.4 0 0.4 0.8
-0.06
-0.02
0.02
0.06
0.1
-0.14 -0.07 0 0.07 0.14
Figure 1: Strange attractor
(left panel) and an enlarge-
ment (right panel) in the
heterogeneous agent asset-
pricing model with evolutionary
learning in Brock and
Hommes (1998). The origin
represents the fundamental
steady state price. Asset prices
deviate from their fundamen-
tal price, jumping irregularly
over the strange attractor.
The right panel illustrates the
complicated geometric, fractal
structure of the strange
attractor around the unstable
fundamental steady state.
The philosophy underlying
our evolutionary approach
is to use simple forecasting
rules and “let evolution
decide who is right.”
Although our evolutionary
model is extremely simple,
the simulated returns series
resembles 40 years of
S&P 500 data.
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tinbergen magazine 3, spring 2001
are highly significant and slowly decaying upto 50 lags, illustrating clustered volatilityand long memory. The right-hand panel infigure 2 illustrates the stylised facts for asimple version of our evolutionary asset-pricing model, with only two types of traders,fundamentalists and technical analysts. Thesimulated time series exhibits unpredictablereturns (almost no significant autocorrela-tions in returns) and clustered volatility andlong memory (with slowly decaying autocor-relations of squared returns and absolutereturns). Although our evolutionary model isextremely simple, the simulated returnsseries resembles 40 years of S&P 500 data.
tionary models give an accurate descriptionof observed asset-price fluctuations, doesthis result imply a certain “forecastability” ofasset returns that could be exploited bysmart traders? In other words, do our modelsrepresent a market that is (close to) efficient?We would like to stress here that theextremely simple non-linear dynamic modelsdiscussed here are not easy to predictbecause of their sensitivity to noise. In orderto illustrate this point, figure 3 shows theforecasting performance of the nearest-neighbour forecasting method applied to thechaotic returns series corresponding to thestrange attractor in figure 1, buffeted with anincreasing level of dynamic noise. This
chaotic returns series has no autocorrela-tions, and returns are therefore unpre-dictable from a linear viewpoint. The optimallinear predictor is therefore the mean, andthe horizontal line at 1 in figure 3 indicatesthe corresponding forecasting errors. Thenearest-neighbour forecasting method looksfor past patterns in the data and predictsthat the next return will be an average ofnearby patterns. As can be seen from thelowest graph in figure 3, this method yieldsexcellent predictions, with errors muchsmaller than those obtained throughprediction by the mean, in the deterministicchaotic case. However, as the level of dynam-ic noise increases, the forecasting errorsrapidly increase to 1, even at shortforecasting horizons. Our simple non-linearevolutionary system thus captures aninherent unpredictability that is so typicalfor financial series.
Future perspectiveEconomics has witnessed important
changes in the last decades, from linearity tonon-linearity, from a theoretical representa-tive agent approach to a computational,multi-agent approach, and from abstract per-fect rationality to bounded rationality mod-els of behavioural economics. Much workremains to be done. At CeNDEF, within theTinbergen Institute, we hope to contribute tothese developments in modern economictheory.
A changing worldAlthough international capital move-
ments have been prominent for quite sometime, it was only during the 1980s that finan-cial markets gradually began to progresstowards a competitive global industry – fol-lowed thereafter by an unprecedented speed-up of this integration. Abetting this processwere the liberalisation of capital accounttransactions, the trend toward increased pri-vate saving for retirement, the developmentof the European Community’s single marketin financial services, and certain bankingreforms in major advanced countries. Grossflows of portfolio and foreign direct invest-ment more than tripled between the mid-80sand the mid-90s, resulting in cross-bordertransactions in bonds and equities that cur-rently surpass the GDP values of mostadvanced countries. The increased mobilityof capital coincided with the growing recog-nition that economies now revolve aroundthe production and use of knowledge. Withthe continuous “upskilling” of jobs, invest-ment in education has become a high priorityin many developed and developing countries.
These realisations, which have led to are-examination of the effects of long-termcapital movements, have also raised someimportant questions: what are the dynamicbenefits of capital markets integration (CMI)in terms of aggregate production and its allo-cation between countries? What are theeffects of CMI on the distribution of incomes
in capital-rich and capital-poor countries?Does the integration of a particular country’seconomy into world capital markets affectthe investment decisions taken by its govern-ment and individual households with regardto education? This review, which examinesthe record to date of the integration of vari-ous countries into the international financial
system (Viaene and Zilcha, 2001a, 2001b),stems from a larger project on dynamic mod-elling of heterogeneous agents in integratedeconomies. The type of international capitalmovement under consideration here involvesa change in the location, but not the owner-ship, of physical capital – a phenomenon thatlies at the heart of the much-disputed global-ization of capital markets. When integrationof capital markets takes place, physical
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tinbergen magazine 3, spring 2001
I n d e p t h
Global challengesof capital markets integration
By Jean-Marie Viaene●
●
Jean-Marie Viaene is
Professor of International
Economics at Erasmus
Universiteit, a Research Fellow
at the Tinbergen Institute, and
a CESifo Research Fellow at
the University of Munich. He
received his M.A. in Economics
from the Faculties of Namur,
and his Ph.D. in Economics
from the University of
Pennsylvania. His current
research focuses on capital
market integration, product
quality effects of trade policy,
and the measurement of mar-
ket power in international
commodity markets.
Does the integration of a
particular country’s economy
into world capital markets
affect the investment decisions
taken by its government and
individual households with
regard to education?
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tinbergen magazine 3, spring 2001
capital literally flows from the low-returncountry to the high-return country untilinterest rates are equalised in the integratedeconomy.
Endogenous growthand free capital flowsThe specific models we analyse inte-
grate several features of the recent literatureon endogenous growth. They provide anextremely efficient analytical tool for study-ing income distribution and growth in, aswell as convergence between, various coun-tries. A central issue in these endogenousgrowth models has been the evolution ofhuman capital (see, e.g., Lucas, 1988;Azariadis and Drazen, 1990). The productionfunction of human capital is a complex mat-ter, since education and learning occur invarious ways. It is not surprising that statis-tical offices of international organisations
compile extensive lists of indicators thatdescribe and compare educational achieve-ments across countries (see, e.g., OECD,1997). While these features vary from coun-try to country (which implies that there maynot be a single theory that characterises allthe observed developments), two main com-mon elements have characterised the pro-cesses of human capital formation. First, theproduction function for human capitalexhibits the property that agents from below-average educational backgrounds have agreater return to human capital investmentderived from public schooling than do thosecoming from above-average human capitalfamilies. Also, the efforts, and therefore thecosts, of acquiring human capital for theyounger generation will be smaller forsocieties that are already endowed with rela-tively higher levels of human capital (see,e.g., Tamura, 1991; Fischer and Serra, 1996).Second, parental tutoring plays an importantrole. For example, Glaeser (1994) divides theeducation’s positive effects on economicgrowth into parts, and concludes that chil-dren in families with educated parents seemto obtain a better education than do thosechildren without that supportive context.
In such frameworks, integration of capi-tal markets between economies does notnecessarily increase the long-run rate of
economic growth. In this regard, the findingcontradicts a common belief in internationaleconomics. However, even in trade theory,the result that trade in goods affects the rateof growth is not robust (see, e.g., Grossmanand Helpman, 1991; Rivera-Batiz and Romer,1991). Generally, trade models with physicalcapital in R&D activities, or those with tradepolicies that increase the stock of knowledge,show changes in the rate of growth. This pro-vides a temptation to modify our frameworkin order to generate growth effects of capitalmarkets integration. However, in contrast tothe visible returns to R&D activities, a largeshare of public spending on educationfinances the (less measurable) human capitalinvolved in the process.
How integration benefits participating countriesAlthough the integration of capital mar-
kets is unable to affect the long-run growthrate, it does, when compared to autarky,affect economic development during thetransition periods. Thus, total output of theintegrated economy after CMI seems to behigher than under autarky at all dates.Likewise, aggregate capital stocks are alsohigher at all dates following integration.Hence, free and perfect capital mobility leadsto overall dynamic gains for the integratedeconomies. Based on numerical simulations,gains in income on the order of 1.5 to2 percent per period are observed in theshort run, with gains fading away quicklythereafter.
Although these results are quite strong,their significance is somewhat limited by twoconsiderations. Since aggregate incomesincrease for all periods after integration,some transfer systems can achieve a Pareto-dominating allocation – with all individualsin integrated economies becoming better-offfollowing capital market integration. This isnot necessarily the case if the competitivemechanism acts alone. Second, there is animplementation paradox: first generations inall integrated countries gain in terms of utili-ty, and will vote in favour of integration,even though some later generations lose.
Division of the gainsAlthough some capital flows are
observed between wealthy and poor coun-tries, the largest part of global direct invest-ment is that among the developed countriesthemselves, rather than between these coun-tries and the less developed. Direct invest-ment is now dominated by Japan, the UnitedStates and the EC – all investing in eachother. An intriguing question raised by Lucas(1990) is why more capital does not flow intopoorer countries. One of our results is that
Even when large discrepancies in educational levels
exist between countries, integration of their capital
markets does not necessarily increase the long-run
rate of economic growth.
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tinbergen magazine 3, spring 2001
each country’s share in total output, andshare in the stock of physical capital of theintegrated economy, is given by its share inthe stock of human capital. Countries thatare poor in human capital thus have a lowshare in total physical capital stocks, andtherefore a low share in total output. Thisresult simply follows from the internationalequalisation of returns to physical capitaland from the properties of neo-classical pro-duction functions.
Competition between governmentsA typical policy advocated by interna-
tional organisations is that developingcountries, in order to capture the benefits of integration into world capital markets,should attract long-term foreign investmentby cultivating a “healthy” economic environ-ment – a process that includes investment inhuman capital. Why? A country that increas-es its investment in education is raising itsmarginal return to physical capital, thusattracting a larger share in the limited globalcapital available for investments. Capitalmarket integration therefore enhances com-petition among governments with regard totheir education policy.
Various solutions to such competition ineducation have been considered. We showthat the “optimal” public education is thesame, regardless of whether governmentsagree on a co-operative solution or a Nashbargaining solution. In contrast, in the Nashequilibrium between any two governments,we obtain a non-Pareto optimal level.
Inefficiencies arise from overinvestment inpublic education, which raises the need forinternational policy co-ordination.
Implications for income distributionIncome distribution is a key economic
issue, and its importance is forcingeconomists and policy makers to sharpentheir understanding of its underlying deter-minants. Evidence of a rise in incomeinequality has been observed in a large num-ber of OECD countries. Some believe thatsocial norms are crucial determinants ofearnings inequality (e.g., Atkinson, 1999).Others maintain that this rise is driven,instead, by events like progress in informa-tion technology and integration of worldtrade and financial markets. Earlier empiricalanalyses confirmed the popular belief thatincome inequality is harmful to economicgrowth (see, e.g., Persson and Tabellini,1994). More recent empirical findings(Forbes, 2000) are inconclusive, however,which is confirmed in our work. Our modelsas they stand allow us to explore the impacton income distribution of various events –such as capital markets integration, orchanges in initial conditions or in thebehavioural relationships bound up by thestrength of familial and societal externalities.To illustrate, international factor movementsalter the relative domestic supplies of pro-ductive capital and, hence, are expected tochange the intragenerational distributions ofincome. Income distributions actually have atendency to change according to the flow ofcapital, resulting in a more equal incomedistribution in the capital-exporting country,and less equal income distribution in thereceiving country at all dates. Although thereis no firm effect on long-term growth rates,capital markets integration clearly impactsthe income distributions of the participatingcountries.
A country’s share in total output, and share in the
stock of physical capital of the integrated economy,
is given by its share in the stock of human capital.
References
Atkinson, A.B., (1999), Is rising
income inequality inevitable?
A critique of the Transatlantic
Consensus, UNO/WIDER Publication
WAL3.
Azariadis, C., and A. Drazen, (1990),
Threshold externalities in economic
development, Quarterly Journal of
Economics 105, 501-526.
Fischer, R.D., and P.J. Serra, (1996),
Income convergence within and
between countries, International
Economic Review 37(3), 531-551.
Forbes, K.J., (2000), A reassessment
of thae relationship between inequal-
ity and growth, American Economic
Review, 90(4), 865-887.
Glaeser, E.L., (1994), Why does
schooling generate economic growth?
Economics Letters 44(3), 333-337.
Grossman, G.M., and E. Helpman,
(1991), Innovation and growth in the
global economy, MIT Press,
Cambridge, MA.
Lucas, R., (1988), On the mechanics
of economic development, Journal of
Monetary Economics 22, 3-42.
Lucas, R., (1990), Why doesn’t capital
flow from rich to poor countries?,
American Economic Review 80(2), 92-96.
OECD, (1997), Education at a glance -
OECD indicators, OECD, Paris.
Persson, T., and G. Tabellini, (1994),
Is inequality harmful for growth?
American Economic Review 84(3),
600-621.
Rivera-Batiz, L.A., and P.M. Romer,
(1991), Economic integration and
endogenous growth, Quarterly
Journal of Economics 106(2), 531-555.
Tamura, R., (1991), Income conver-
gence in an endogenous growth
model, Journal of Political Economy
99, 522-540.
Viaene, J.-M., and I. Zilcha, (2001a),
Capital markets aintegration, growth
and income distribution, European
Economic Review, forthcoming.
Viaene, J.-M., and I. Zilcha, (2001b),
Public education under capital mobil-
ity, Journal of Economic Dynamics
and Control, forthcominag.
11
Development economics is a vast field,covering topics in microeconomics andmacroeconomics. Do you have a preferencefor either one?
I’m interested in both, actually. Onetopic that is sort of in-between the two istrade shocks: the economic impact of violentchanges of commodity prices on world mar-kets. The macroeconomic side of that has todo with a shock’s balance of paymentsimpact and its impact on government bud-gets and debt positions. Its microeconomicimpact concerns saving behaviour. For a long
time economists have argued that smallhold-er households (households of farmers withvery small areas of land) would not respondto shocks in an economically rational way.A lot of my early research used survey datato see whether that is true or not. It is nowclear that even poor, illiterate farmers willsave in response to positive shocks. This haschanged the attitude of governments towardstaxation of agricultural products. This pro-cess is, I think, central in the field of devel-opment economics. You take a policy ques-tion on which you need economic evidence,
Up
close
by Bert Hof
An interview with development economist
Jan Willem Gunning
Modern economics in action
in poor countries
Jan Willem Gunning is Professor in the
Department of Economics at the Vrije
Universiteit Amsterdam, and heads the
Development Economics Section.
He is also director of the Amsterdam
Institute for International
Development.
12
tinbergen magazine 3, spring 2001
like: should the government isolate house-holds from world shocks, or not? You thenformulate a hypothesis based on microeco-nomic theory, and use survey data to testthat theory econometrically.
What distinguishes development economicsfrom economics in general?
Development economics applies thetools of modern economics to situations inwhich markets function imperfectly, or donot exist. For example, property rights maynot have been established, or infrastructuremay not function very well. This has implica-tions for the functioning of economic agents.This may not be an issue in most advancedeconomies.
What are your current research interests?I’m working on the functioning of
African labour markets and on the effect ofaid on domestic taxation. Concerning the lat-ter, what donors would like to see is thattheir money is not used as a substitute forraising taxes domestically. They encouragegovernments to raise more taxes, partly as acondition for aid. There are good theoreticalreasons why that might be a bad combina-tion. The costs resulting from distortionsyou impose on the economy might be quitehigh in developing countries. I am investigat-ing whether aid can actually be harmful byimposing these costs of taxation. It’s a theo-retical question, but one that’s directly relat-ed to policy debates.
Much of your work has been on Africa. Why is Africa so special?
Poverty is very much an African prob-lem, and increasingly so. A lot of the povertyin Latin America and East Asia has disap-peared. There are still poor people there, butfar less than a generation ago. South Asia hasthe largest number of poor people, but itappears to be rapidly moving out of poverty.Africa has the largest percentage of the pop-ulation below any poverty line you can imag-ine. What I foresee is that poverty in SouthAsia will continue to decline, and that inAfrica it will remain much more entrenched.Such a grim prospect is motivation enoughfor trying to understand the nature of theproblems there.
Does economic research explain why peopleare poor?
I think so. We can’t provide completeanswers, but we can clarify what the maindeterminants of poverty are, so that we areat least not barking up the wrong tree.I think that is a modest position. We’re notgoing to change the world, but we might beone of the helping hands.
How? Well, publishing an article is not going
to end poverty in Burkina Faso, but it mightinfluence thinking, and eventually lead topolicies that do change poverty in BurkinaFaso. Like Keynes, I believe in the power ofideas. As academics, we are often too cynicalabout the effects of our own work. I thinkthat’s wrong; ideas can often be traced toacademic work, and can influence policymakers both in developing countries and indonor agencies. That’s why economicresearch is so important.
Can you give an example of research leadingto changes in policy – for the better, that is?
Well, consider the case of trade shocks:the dominant policy adopted by almost alldeveloping countries, and with the blessingof the World Bank, was to insulate producersfrom shocks by stabilising export taxes forcommodities like coffee, tea, and tobacco.That policy has now been abandoned almosteverywhere, and the World Bank has explicit-ly referred to the microeconomic evidence insupport of changing the policy. I’m not claim-ing that because of my research, and that ofcolleagues, we have changed poverty inUganda, but I am saying that our researchhas certainly contributed to the policychange. Some of the rapid poverty reductionswe see in Uganda have been caused by farm-ers getting better prices – as a result of thechange in policy.
Which developments within development eco-nomics research do you see occurring?
I see the focus on microeconomics andapplied econometrics getting stronger.There’s also an increasing awareness that weneed formal policy analysis. The textbookargument that the removal of a single distor-tion is welfare increasing is not very helpfulwhen there are many distortions: second-best problems are important in developmenteconomics. Take the issue of sequencing, forexample. We’ve come to realise that you haveto think very carefully about the order inwhich you take liberalisation measures. TheWorld Bank and the IMF are now really focus-ing on those issues. If you want to do thatwell, you need a model of the economy.Sometimes it is simple – you can do it on theback of an envelope – but often it’s not.
Like Keynes, I believe in the power of ideas.
As academics, we are often too cynical
about the effects of our own work.
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tinbergen magazine 3, spring 2001
Regarding Africa, there has been an enor-mous debate on whether structural adjust-ment was good for poverty elimination ornot. That debate has been partly resolved byusing general equilibrium models as a sort oflaboratory in which you test the effect onvarious groups in the society. I envision sim-ulation exercises using general equilibriummodels as becoming more important.
What is the way out of poverty for Africa? Typically, poverty goes down in the
presence of economic growth. Another wayof asking the question is: why isn’t theremore growth? This is where microeconomicresearch plays a role – by telling you some-thing about the environment and behaviourof firms. Part of the answer is that, in manyAfrican countries, the state has been veryactive in doing the wrong sort of things, liketrying to take over the manufacturing sector.It has very often neglected its more tradition-al roles, notably the provision of infrastruc-ture and a viable legal system. These arereally important, because high transportcosts or inefficient ways of settling claimsbetween people can stop investments fromtaking place. Why the state has not provided
the necessary infrastructure and legal systemis a question of political economy. Particulargroups that do not want the state to have agood legal system, or build high qualityroads in rural areas, but want to use thestate for their own interests instead mayhave captured the state.
A related issue is the enormous risk pre-sent in many African economies. Some of therisk cannot be controlled, like the risk of theweather, or volatility of world prices.However, policy risk also plays a role. Thegovernment may make certain policy state-ments, for example, but has insufficientcredibility for investors to believe them.
Consider the uncertainty surrounding futureeconomic policies, taxation, internationaltrade, and price controls. If you look at inter-views of investors, both domestic and for-eign, you see that such abnormal risk cansimply put a halt to investment. Here, Ithink, the traditional macroeconomist whoemphasises the importance of stability isright. It is important to have a stable regimethat is also perceived as being stable. We arebeginning to get that in a few African coun-tries, but it is still a very small number.
What should rich countries do, in youropinion, with respect to their policies towardsdeveloping countries?
A lot of the debate has focused on aidflows. That debate has changed enormouslyin the last five years. It has become clear thatrich countries have allocated aid over coun-
Some of the rapid poverty reductions we see
in Uganda have been caused by farmers
getting better prices – as a result of the
change in policy.
Has structural adjustment been good for
poverty elimination in Africa? That debate
has been partly resolved using general
equilibrium models.
Value of a
statistical life
To properly evaluate trafficaccident costs (concerningfatalities, for instance) froman economic perspective,which is necessary toachieve a rational and effi-cient allocation of public andprivate (safety) budgets, weneed an estimate of the eco-nomic Value Of a StatisticalLife (VOSL). The VOSL isdefined as the normalisedvaluation of a change in risklevels (rather than the valua-tion of the life of a specificindividual). Since the 1970’s,numerous studies have esti-mated the VOSL in road safe-ty, using stated and revealedpreference methods. Thesestudies were carried out indifferent countries and in dif-ferent years, resulting in awide range of estimates,going all the way from150,000 up to 30 million USdollars. We have used meta-analysis to determine if thereare factors that systematical-ly affect the VOSL estimates.Meta-analysis offers a set ofquantitative techniques thatpermit synthesising theresults of different empiricalstudies, which, in this paper,are studies estimating theVOSL in the context of roadsafety.From this study we concludethat a common VOSL, evenfrom a theoretical perspec-tive, does not exist. Apartfrom presenting the safetygood in differing ways (pub-
lic vs. private good), theVOSL depends on the initialrisk level of a (fatal) acci-dent, and on the risk declineconsidered. These variableshave a far greater explana-tory power than more generalbackground variables suchas GDP per capita.
Arianne de Blaeij,
Raymond J.G.M. Florax,
Piet Rietveld and Erik T. Verhoef
(VU), “The Value of Statistical
Life in Road Safety:
A Meta-Analysis”
TI 00-89/3
Managing
exchange
rate risk
Until the time that the worldis united, or at least usingone common currency, firmsthat operate in internationalwaters will continue to runthe risk that the value oftheir foreign investments willchange due to fluctuations inthe exchange rate. Thesefluctuations can be large:The US dollar, for example,which appreciated 7.5% com-pared to the German D-Markin 1998, appreciated abouttwice as much during theyear 1999.Firms can decide to hedgetheir currency risk. Insteadof accepting the uncertainvariation in the exchangerate, the firm pays the differ-ence between the foreignand the national risk-freeinterest rates. This paperdevelops a framework toassist the manager, on adaily basis, in decidingwhether or not to hedge.The decision is based onoptimizing a utility functionas a function of the hedgeratio, using the predictivedistribution of tomorrow’sexchange rate return asinput. For a range of sevenmodels, we construct thispredictive distribution usingBayesian methodology. In
14
tinbergen magazine 3, spring 2001
tries in a very inefficient way. This makes ithardly surprising that a lot of people say that“aid does not work”. It is to some extent true,but is largely the result of giving money togovernments that are unlikely to do some-thing sensible with it. Some of the rich coun-tries are therefore changing their aid policies.Probably more important, though, is theopening of markets. There still is a lot of pro-tection in rich countries. Agriculture andclothing and textiles are good examples. Wehave said, for more than a generation, that
these exports are vital to developing coun-tries and that we will open our markets. Yet,we keep postponing the opening, which hin-ders development in these countries.
Are you optimistic about the futureof Africa?
If all of our impressions of Africa comefrom television, which emphasises thefamines and war that take place, we miss animportant point. Some countries have made alot of progress, which gets very little publi-city. A small economy like Botswana has beenthe top country in terms of economic growthfor a long time now, Uganda is doing verywell, and quite a few other countries have hit6-7 percent growth rates. Sustained growth isthe challenge – particularly for the largereconomies, because at the moment the moresuccessful countries are typically the smallereconomies. What would really “make head-lines” is a country the size of Nigeria takingoff – but that’s not happening yet. So, toanswer your question: I am optimistic, butonly mildly so.
discussionpapers
In Africa, the challenge
is sustained growth –
particularly for the larger
economies.
References
Collier, P. and J.W. Gunning, (1999), “Explaining African
Economic Performance”, Journal of Economic Literature,
vol. 37, pp. 64-111.
Collier, P. and J.W. Gunning, (1999), Trade Shocks in
Developing Countries; Volume 1: Africa. Volume 2: Asia
and Latin America, Oxford: Oxford University Press,
vol. 1: pp. ix, 491, vol. 2: pp. ix, 360.
Fafchamps, M., J.W. Gunning, and R. Oostendorp, (2000),
“Inventories and Risk in African Manufacturing”,
Economic Journal, vol. 110, pp. 861-893.
15
tinbergen magazine 3, spring 2001
this way, we can incorporateparameter uncertainty andfilter out the little informa-tion the data contains abouta local trend in the exchangerate, thus also obtaining aprediction of the uncertaintyof tomorrow’s return.During the evaluation period1998-1999, one of the sevenmodels – with varying vari-ance (stochastic volatility)and an unobserved localtrend – fits the data best.The model is good at guid-ing the risk manager in tak-ing the decision to hedgecurrency risk in periods ofhigh risk of depreciation,while also helping him toavoid missing out on thepossible profits during peri-ods of a rising exchangerate.
Charles S. Bos, Ronald J.
Mahieu, Herman K. van Dijk
(EUR), “Daily Exchange Rate
Behaviour and Hedging of
Currency Risk”
TI 01-017/4
Trade-offs in
employment
relations
In the fast-food industry, twodifferent types of labourrelations exist side-by-side: afixed-wage employment con-tract with perfect insurance,and a franchising arrange-ment, whereby the worker isthe owner who takes all therisk. How do we explain theco-existence of two such
widely different organisa-tional principles? This paperexplores the role of the non-verifiability of output. Withnon-verifiable output, firmscan only insure workerswhen they are entitled to allof the worker’s output. Ifnot, workers would only selltheir output to the firm inbad states of nature. In goodstates of nature, workerswould sell the output on themarket. An employment rela-tion with production takingplace within the firm guaran-tees that workers delivertheir output to the firm, inboth good and bad states ofnature. However, by organis-ing production in a firm-spe-cific employment relation,new contracting problemsarise, which have been previ-ously analysed by Macleodand Malcomson (1989).Firms can claim that workershave not provided effort,and therefore refuse to paytheir wages. Since output isnon-verifiable in a court oflaw, the wage payment bythe firm must be self-enforc-ing. A trade-off thereforeexists between the gainsfrom insuring risk-averseworkers and the transactioncost of a self-enforcing con-tract. We show that competi-tion from the market maylead to excessive flexibilityand to the crowding-out ofwelfare-improving fixed-wage employment relations.
A. Lans Bovenberg (KUB),
and Coen N. Teulings (EUR),
“Insurance and Information:
Firms as a Commitment Device”
TI 01-020/3
Modelling
investment
strategies
This paper presents a gener-al dichotomous model foranalysing and pricing invest-ment strategies. Unifyingmodern portfolio theory andoption pricing theory, itshows that inherent efficien-cy (or the absence ofapproximate arbitrage)implies a unique price forany investment strategy –expressed as the sum of twoseparate values: its up-market discounted value andits down-market discountedvalue. Since financial assetsare essentially special buy-and-hold strategies, themodel encompasses virtuallyall known European-typederivative-pricing models(see, e.g., Black and Scholes,1973). More importantly, themodel allows firms and indi-viduals to evaluate rigorous-ly those investment strate-gies for which the complete-market hypothesis does nothold – for example, wheredecisions involve realoptions.Among the dichotomousmodel’s empirically testablepredictions are a pair of lin-ear equilibrium relationshipsbetween each security’s up-market (down-market) poten-tial and the market’s inherentreward (inherent risk). Thesepredictions are stronger thanthose of other equilibriummodels (e.g., mean-vari-ance), and are hence moreverifiable. Other issues dis-cussed in the paper includethe non-negative wealth con-straint, individual optimality
with dichotomous utilityfunctions, heterogeneousbeliefs in market directions,quasi-complete markets, flatoptions, Pareto efficiency,and the existence of equilib-rium. The theoretical founda-tion is laid in a precedingpaper (Zou, TI 2000-50/2).
Liang Zou (UvA), “Inherent
Efficiency, Security Markets,
and the Pricing of
Investment Strategies”
TI 00-108/2
All discussion papers
can be downloaded via
www.tinbergen.nl
16
tinbergen magazine 3, spring 2001
Linkages
to social
efficiency
V. Bala andSanjeev Goyal (EUR)
Traditionally, economistshave sought to explainsocial and economic phe-nomena using an approachbased on individual optimi-sation, where the individualsare located in centralisedsettings and interact anony-mously. Perhaps the mostclassic example of thisapproach is the analysis ofthe nature of equilibrium incompetitive markets witha large number of players.Recently, researchers havebegun to analyse the moregeneral forms of interactionbetween individuals – therole of social structure, forexample. This work hasrevealed, first of all, thatnon-market aspects of inter-action are central to under-standing a variety of phe-nomena. The research hasalso indicated some routesthrough which the influenceof interaction may work. Yet the question remains:which forms of interactionare plausible?
Count the costs…To address this question, weconceptualise interactionstructures as networks –with individuals as nodes,and their relations as links.In many settings of interest,individuals themselves shapethe nature of their interac-tion with others. We are thusable to postulate that socialand economic networks areformed by individual deci-sions that trade-off the costsof forming and maintaininglinks against the potentialrewards from doing so. Inour study we suppose thatone individual’s link with
another allows access – inpart and in due course – tothe benefits available to thelatter via his own links.Thus, individual links gener-ate externalities for others.We suppose that the costs oflinks are borne by the play-ers who initiate the links,and this assumption allowsus to formulate the networkformation game as a non-cooperative game.
Narrow downthe options…Our results indicate thatstrategic incentives to bal-ance the costs and benefitsof links sharply limit thenature of network architec-tures that can arise. We nar-row down the possibilitiesfor equilibrium networks(under fairly general condi-tions) to two configurations:they are either wheels (witha single cycle connecting allindividuals) or stars.Interestingly, we find that ifindirect links are as good asdirect links, then the cen-tre/hub of a star pays for allthe links, while if indirectlinks are less valuable thandirect links, then thespokes/peripheral playerspay for the links as well. Wethen examine the dynamicsof network formation, andfind that individuals learnrapidly and that the dynamicprocess converges to theequilibrium networks identi-fied earlier. Finally, we showthat strategically stable net-works in many of the set-tings we study are alsosocially efficient.
Bala, V., and S. Goyal (2000),
A Noncooperative Model of
Network Formation,
Econometrica; 68(5),
September 2000,
pp. 1181-1229.
Emotions as
a new source
of efficiency
costs?
Ronald Bosmanand Frans van Winden(UvA)
Psychological research hasshown that emotions areimportant for many psycho-logical processes, like learn-ing, attention, and memory.Recent neuroscientificresearch even suggests thatemotions are important forrational decision making.Economists, however, havethus far neglected the role ofemotions in their research.Our study investigateswhether emotions are impor-tant for economic decisionmaking. We start with a two-player power-to-take gamethat models in a simple butfundamental way situationsin which one agent can(potentially) appropriate partof the endowment of anoth-er. This game capturesimportant aspects of taxa-tion, principal-agent relation-ships, and monopoly pricing.In the area of taxation, forexample, an owner of a pro-duction factor could dimin-ish the supply of this factorif he or she feels that the taxon the returns of this factoris outrageous.
In the experiment, playersearn an income in an individ-ual effort task preceding thepower-to-take game. Thegame itself consists of twostages.
First, one player (the take-authority) can claim any partof the income of the otherplayer (the responder). In thesecond stage, the latter play-er can respond, perhaps bydestroying his own income.The transfer of money isbased on what is left afterthe second stage.Responders can punishgreedy take-authorities bydestroying their own earnedincome. We focus on howemotions influence respon-der behaviour. The resultsshow the following: (1) ahigher take rate increasesthe intensity of negativeemotions (such as irritation,contempt, and envy), anddecreases the intensity ofpositive emotions (like hap-piness and contentment); (2)negative emotions drivedestruction; (3) at momentsof high emotional intensity,responders destroy eithernothing or everything; (4)responder expectationsregarding the response ofthe take-authority affect theprobability of punishment.Because destruction of ownearned income is inefficient(scarce resources are beingdestroyed), emotionalhazard is identified as a newsource of efficiency costs.
Bosman, R., and F. van Winden,
Emotional hazard in a
power-to-take experiment
(forthcoming in the
Economic Journal).
papers in journals
17
tinbergen magazine 3, spring 2001
Banishing
naiveté
Frank A.G. Den Butter(VU) and Mary S.Morgan (UvA)
The interactionbetween economicmodellers and policymakers
The tenth anniversary ofthe Tinbergen Institute wascelebrated with a researchconference on a topic thatwas close to the heart of theInstitute’s namesake? Theconference focused on howeconomic models are usedin the policy process andbrought together prominenteconomists and policymak-ers from nine countries.
The naive view of economicmodels that aim to influencepolicy maintains thateconomists use models toproduce advice, which maybe either rejected or accept-ed by policymakers.Actually, a more sophisticat-ed two-way interactionbetween modellers and poli-cymakers has been widelyrecognised by thoseinvolved, but has hardlybeen discussed, let alonebeen the subject of academicresearch.
Economic models lie at theheart of any successful inter-action between economicmodellers and policymakers,enabling both parties tomake use of their compara-tive knowledge. But the insti-
tutional context is equallyimportant, for while manydifferent kinds of modelshave dual purposes – provid-ing knowledge as well as theopportunity of negotiationbetween the parties – theywill miss the mark unlesscommunication and trustexist between the twogroups. Thus, different insti-tutional contexts affect theinteraction process. Therange of experiences in vari-ous countries, from Norwayto the Netherlands, fromCanada to New Zealand, sup-ports the conclusion thatthere is no single institution-al formula for success.
What does it take?Fruitful interaction betweenpolicymakers andeconomists through econom-ic models takes many forms.For example, the US FederalReserve’s Open MarketCommittee operates with aformal presentation of mod-elling results followed by aninformal and wide-rangingdiscussion of the results inwhich model assumptionsare brought into questionand requests for new modelelements are made. J.J.Polak, one-time researchassistant to Jan Tinbergen,and founder of the long-standing IMF model toassess its country pro-grammes, maintains that theflexibility and size of hismodel have been critical toits usefulness in countrieswhere local policymakersneed to be persuaded totake unpopular measures.The small size and simplerelations of the model makeit easy to understand, thusproviding the basis forexplaining policies to non-
economists; the model alsomakes minimal demandsregarding data, rendering itappropriate for many unde-veloped economies.
Behind the sceneshumourThe individual case studiesfound in the report makeideal teaching material, andsummary material can befound in the two concludingchapters. Of particular inter-est is the transcript of thestimulating panel discussionin which three eminenteconomists, encouraged byRuud Lubbers (former Dutchprime minister and currentlyUN High Commissioner forthe Refugees), recall tenseand humorous moments during policy arguments.For example, Lisa Lynchdescribes how differencesbetween economic modelpredictions played a criticalrole in first creating and thenresolving the famous bud-getary problems that led tothe Federal Governmentshutdown in the US in1995/6. Edmond Malinvaudlooks back on how politi-cians thought they could dobetter than economists insolving the problem ofstagflation in the early1970s, while Henk Don pon-ders the question of how toeducate political interests sothat they won’t worry aboutthe second decimal place ofa model forecast!
The full report of this research
conference is found in
Empirical Models and
Policy-Making: Interaction and
Institutions (Routledge, 2000, in
paperback). Edited by Frank
den Butter and Mary S. Morgan.
Dealing with
exchange rate
models
According to the asset market view on foreignexchange markets, exchangerates can be seen as the pre-sent value of expectedfuture values of macroeco-nomic variables, such asmoney supplies and realincomes. Under a floatingexchange rate regime, thisasset market view impliesthat new information regard-ing future money suppliesand real incomes, howeversmall, can induce largeexchange rate fluctuations.This, in combination withphenomena such as stickygoods prices, results insizeable and long-lastingdeviations between floatingexchange rates and theaforementioned macro-economic variables.
As data on floating exchangerates are available only from1973 onwards, our difficultyin empirically corroboratingthe asset market view onexchange rates is hardly sur-prising, given the above-mentioned long-lasting devi-ations. To circumvent this,we combine the data onexchange rates and mone-tary fundamentals for a largenumber of industrialisedcountries into a panel dataset.
For example, we test theempirical validity of themonetary exchange ratemodel on a sample of bilat-eral exchange rates andmonetary fundamentals of14 OECD countries, relativeto both the US dollar and theGerman Mark. The testresults for each of the bilat-eral exchange rates sepa-rately provided no evidencesupporting this monetary
For a complete list of recent
discussion papers and theses,
see further in this issue
otherpublications theses
18
tinbergen magazine 3, spring 2001
model. However, after com-bining the time series for the14 above-mentioned bilateralexchange rates into a paneldata set, we found ampleevidence in favour of themonetary exchange ratemodel–irrespective of thechoice of base country.
Thesis: “Testing multi-country
exchange rate models”
By Jan J.J. Groen.
Published in the Tinbergen
Institute Research Series #230.
Exploring the
utilisation
of long-term
care in the
Netherlands
Long-term care services, amajor component of theDutch healthcare system,currently account for 23% oftotal Dutch healthcareexpenditures, and amountsto 7 billion dollars per year.As the expected growth ofthe elderly population willcertainly increase thedemand for long-term careprovision, availableresources will obviously bestretched. Available evidencesuggests that the Dutchlong-term care system is cur-rently supply-constrained.Recent national publicationshave reported that approxi-mately 29,000 Dutch elderlyindividuals are currentlywaiting for home care, and15,000 for placement in acare facility. Given this back-
log, we must question thesustainability of the existinglong-term care system.Sensible reforms requireinsights into how the elderlyactually use the long-termcare services that are avail-able. The primary aim of thiswork is to provide a betterunderstanding of this pro-cess by providing a solideconomic framework andtesting it econometrically.The process by which long-term care services areaccessed in the Netherlandsis highly complex and canbe studied from many differ-ent angles. The dissertation focuses onfour core elements of theprocess: characterisation ofhealth status, calculation ofage- and gender-specific lifeexpectancies in specifichealth states, determinantsof utilisation of long-termcare services conditional onthe recognition of a need forcare, and finally, the processof allocation of care by statecommittees. Changes inhealth status obviously playa central role in the evolu-tion of the demand for careservices. The paper derives atypology of the health statusof elderly persons, whichincludes six dimensions: res-piratory diseases and/or can-cer, other chronic diseases(these diseases are generallyless serious and not specificto the elderly), cognitiveimpairment, serious arthritis,cardiovascular diseases, andno health problems. Policymakers using thishealth typology would find iteasier to determine wherethe costs are highest. Thiskind of information willbecome increasingly impor-tant as the population ages.
Thesis: Long-term care services
for the Dutch elderly;
An investigation into the
process of utilization.
By France Portrait.
Published in the Tinbergen
Institute Research Series #237.
Discussion papers
Institutions and decision processes
00-087/1
Maarten C.W. Janssen, and Ewa Mendys, Erasmus
University Rotterdam, Adoption of Superior
Technology in Markets with Heterogeneous Network
Externalities and Price Competition
00-092/1
Sanjeev Goyal, Erasmus University Rotterdam,
Sumit Joshi, George Washington University,
Networks of Collaboration in Oligopoly
00-093/1
Sanjeev Goyal, Erasmus University Rotterdam,
Fernando Vega-Redondo, Universidad de Alicante,
Learning, Network Formation and Coordination
00-094/1
Arno Riedl, and Frans A.A.M. van Winden,
University of Amsterdam, Does the Wage Tax System
cause Budget Deficits?
00-106/1
Ronald Bosman, University of Amsterdam, Matthias
Sutter, University of Innsbruck, Frans van Winden,
University of Amsterdam, Emotional Hazard and
Real Effort in a Power-to-Take Game
00-107/1
Nicholas Bardsley, University of Amsterdam,
Control without Deception
00-109/1
Maarten C.W. Janssen, and Vladimir Karamychev,
Erasmus University Rotterdam, Continuous Time
Trading in Markets with Adverse Selection
00-111/1
Nicholas Bardsley, University of Amsterdam,
Peter G. Moffatt, University of East Anglia, An
Econometric Analysis of Voluntary Contributions
00-112/1
Arno Riedl and Frans van Winden, University of
Amsterdam, An Experimental Investigation of Wage
Taxation and Unemployment in Closed and Open
Economies
01-003/1
Ingrid Seinen, Arthur Schram, CREED, University of
Amsterdam, Social Status and Group Norms
01-004/1
Valeri Vasil’ev, Sobolev Institute of Mathematics,
Russia, Gerard van der Laan, Vrije Universiteit
Amsterdam, The Harsanyi Set for Cooperative TU-
Games
19
01-011/1
Gerard van der Laan, Vrije Universiteit Amsterdam,
Pieter Ruys, and Dolf Talman, Optimal Provision of
Infrastructure using Public-Private Partnership
Contracts
01-013/1
Cars H. Hommes, University of Amsterdam,
J. Barkley Rosser, Jr., James Madison University,
Consistent Expectations Equilibria and Complex
Dynamics in Renewable Resource Markets
01-014/1
Cars H. Hommes, University of Amsterdam,
Financial Markets as Nonlinear Adaptive
Evolutionary Systems
01-015/1
Andrea Gaunersdorfer, University of Vienna,
Cars Hommes, Florian O.O. Wagener, University of
Amsterdam, Bifurcation Routes to Volatility
Clustering
01-016/1
Peter Boswijk, Gerwin Griffioen, and Cars Hommes,
University of Amsterdam, Success and Failure of
Technical Trading Strategies in the Cocoa Futures
Market
01-022/1
Arjo Klamer, Erasmus University Rotterdam, and
Hendrik P. van Dalen, Erasmus University
Rotterdam, and Scientific Council for Government
Policy, Attention and the Art of Scientific Publishing
01-034/1
Eduardo L. Giménez, Universidade de Vigo,
Complete and Incomplete Markets with Short-Sale
Constraints
01-040/1
Ioulia V. Ossokina, and Otto H. Swank, Erasmus
University Rotterdam, How Polarization and Political
Instability affect Learning through Experimentation
01-041/1
Harold Houba, Vrije Universiteit Amsterdam, and
Alexander F. Tieman, Vrije Universiteit Amsterdam
and De Nederlandsche Bank, Idiosyncratic and
Aggregate Time-Varying Mutation Rates in
Coordination Games
01-044/1
René van den Brink, Tilburg University, Gerard van
der Laan, Vrije Universiteit Amsterdam, A Class of
Consistent Share Functions for Games in Coalition
Structure
Financial and InternationalMarkets
00-085/2
Mark Hallerberg, University of Pittsburgh, Lúcio
Vinhas de Souza, Erasmus University Rotterdam,
The Political Business Cycles of EU Accession
Countries
00-097/2
Eric J. Bartelsman, Vrije Universiteit Amsterdam;
Roel M.W.J. Beetsma, University of Amsterdam, and
CEPR, Profit Shifting and Productivity
Mismeasurement
00-103/2
Michael R. Baye, Indiana University, Dan Kovenock,
Purdue University, Casper G. de Vries, Erasmus
University Rotterdam, Comparative Analysis of
Litigation Systems: An Auction-Theoretic Approach
00-105/2
Enrico Perotti, and Silvia Rossetto, University of
Amsterdam, Internet Portals as Portfolios of Entry
Options
00-108/2
Liang Zou, University of Amsterdam, Inherent
Efficiency, Security Markets, and the Pricing of
Investment Strategies
00-110/2
José Luis Moraga and Jean Marie Viaene, Erasmus
University Rotterdam, Trade Policy of Transition
Economics
01-001/2
Hans Hoogeveen, Vrije Universiteit Amsterdam,
Evidence on Informal Insurance in Rural Zimbabwe
01-002/2
Casper van Ewijk, University of Amsterdam and
CPB, Paul Tang, CPB, Efficient Progressive Taxes and
Education Subsidies
01-019/2
Enrico C. Perotti, University of Amsterdam, and
CEPR, Ernst-Ludwig von Thadden, Université de
Lausanne, and CEPR, Outside Finance, Dominant
Investors and Strategic Transparancy
01-021/2
André Lucas, Vrije Universiteit Amsterdam, Ronald
van Dijk, ING Investment Management, and Tilburg
University, Teun Kloek, Erasmus University
Rotterdam, and ING Investment Management, Stock
Selection, Style Rotation, and Risk
01-023/2
André Lucas, Vrije Universiteit Amsterdam,
Pieter Klaassen, ABN AMRO Bank NV, Peter Spreij,
University of Amsterdam, and Stefan Straetmans,
Maastricht University, Tail Behavior of Credit Loss
Distributions for General Latent Factor Models
01-033/2
Wilfred J. Ethier, University of Pennsylvania,
Unilateralism in a Multilateral World
01-035/2
Silvia Caserta, Antonio Paolo Russo, Erasmus
University Rotterdam, More means Worse –
Asymmetric Information, Spatial Displacement and
Sustainable Heritage Tourism
01-037/2
Neelam Jain, Rice University, Thomas D. Jeitschko,
Texas A&M University, Leonard J. Mirman,
University of Virginia, Financial Intermediation and
Entry Deterrence
01-043/2
Ronald J. Balvers, Douglas W. Mitchell, West Virginia
University, USA, Reducing the Dimensionality of
Linear Quadratic Control Problems
20
Labour, Region and Environment00-081/3
Marthen L. Ndoen, Cees Gorter, Peter Nijkamp,
Piet Rietveld, Vrije Universiteit Amsterdam,
Migrants Entrepreneurs in East Nusa Tenggara
00-082/3
C. Gorter, Vrije Universiteit Amsterdam, Migrant
Entrepreneurs in East Indonesia: A Schumpeterian
Perspective
00-083/3
Katrin Oltmer, Peter Nijkamp, Raymond Florax, Vrije
Jeroen C.J.M. van den Bergh, and Justin M. Holley,
Vrije Universiteit Amsterdam, An Environmental-
Economic Assessment of Genetic Modification of
Agricultural Crops
01-026/3
Erik T. Verhoef, Jan Rouwendal, Vrije Universiteit
Amsterdam, A Structural Model of Traffic Congestion
01-027/3
Arianne de Blaeij, Daniel van Vuuren, Vrije
Universiteit Amsterdam, Risk Perception of Traffic
Participants
01-028/3
Thomas de Graaff, Cees Gorter, Peter Nijkamp,
Vrije Universiteit Amsterdam, Effects of Ethnic
Geographical Clustering on Educational Attainment
in the Netherlands
01-030/3
Ingrid Verheul, Erasmus University Rotterdam and
EIM, Sander Wennekers, EIM, David Audretsch,
Indiana University, Roy Thurik, Erasmus University
Rotterdam and EIM, An Eclectic Theory of
Entrepreneurship: Policies, Institutions and Culture
01-036/3
Henri L.F. de Groot, Vrije Universiteit Amsterdam,
Cees A. Withagen, Tilburg University, CentER, Vrije
Universiteit Amsterdam, Zhou Minliang, Institute of
Industrial Economics, Chinese Academy of Social
Sciences, Dynamics of China’s Regional Development
and Pollution
01-038/3
Jan de Kok, Erasmus University Rotterdam, Lorraine
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Eastern Michigan University, Organization Context
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232 M.L. NDOEN (19-09-2000), Migrants and
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A socioeconomic model of profit-seeking behaviour.
233 L.A. GROGAN (28-11-2000), Labour market
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234 E.G. VAN DE MORTEL (15-12-2000),
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235 P.H. VAN OIJEN (27-10-2000), Essays on corpo-
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236 H.M.M. VAN GOOR (20-12-2000), Banken en
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237 F.R.M. PORTRAIT (31-10-2000), Long-term care
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238 M. VAN DE VELDEN (07-11-2000), Topics in cor-
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239 G. DRAISMA (11-01-2001), Parametric and semi-
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240 I.F.C. MULDER (06-02-2001), Soil degradation in
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241 A.W. SALY (05-04-2001), Corporate
entrepreneurship. Antecedents and consequences of
entrepreneurship in large established firms.
242 S. VAN VELZEN (06-02-2001), Supplements to
the economics of household behavior.
243 R.A. VAN DER GOOT (19-01-2001), High
performance linda using a class library.
244 E. KUIPER (08-02-2001), The most valuable of
all Capital. A gender reading of economic texts.
245 P. KLIJNSMIT (01-03-2001), Voluntary corporate
governance disclosures; An empirical investigation
of UK practices.
246 P.J.G. TANG (29-03-2001), Essays on economic
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247 H. HOOGEVEEN (26-04-2001), Risk and
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248 A.J. VAN DER VLIST (22-05-2001), Residential
mobility and commuting.
23
tinbergen magazine 3, spring 2001
tinbergen institute
Tinbergen Research InstituteFour themes distinguish Tinbergen
Institute’s research programme:I. Institutions and Decision AnalysisII. Financial and International MarketsIII. Labour, Region and the Environment IV. Econometrics and Operations Research
Each theme covers the whole spectrum ofeconomic analysis, from theoretical to empiri-cal research. Stimulating discussions on theories, methodologies and empirical resultsarise from the interaction of the Institute’sfaculty – comprised of approximately 85research fellows. These fellows are facultymembers with excellent track records in eco-nomic research, active in organising researchactivities, teaching graduate courses andsupervising Ph.D. students.
Discussion PapersResearch is pre-published in the institute’s
own Discussion Paper Series. Download discussion papers at http://www.tinbergen.nl(section ‘Publications’). E-mail address for correspondence: [email protected]
Tinbergen Graduate SchoolThe Tinbergen Graduate School enrols
about 145 students in two programmes. Oneleads to a Master of Philosophy in economics,and the other to a Ph.D. in economics.
Master of Philosophy programmeTinbergen Institute’s intensive one-year
Master’s programme leads to a Master ofPhilosophy in economics. Both those studentsaiming for a Ph.D. in economics, as well asthose pursuing careers in top consulting- orpolicy advice organisations, stand to benefitfrom the excellent preparation offered by theprogramme. Core courses are offered in thefollowing: microeconomics, macroeconomics,mathematics for economists, econometrics,advanced econometrics, and organisation.Specialised courses are offered in the follow-ing: international trade and development,monetary economics, finance, labour eco-nomics, public economics, microeconomictheory and game theory.
Ph.D. programmeFour years of solid training in the princi-
ples of economics and econometrics (based onlectures, workshops, seminars and examina-tions), as well as the successful completion ofa supervised doctoral thesis, provide the basisfor Tinbergen Institute’s Ph.D. programme.The programme’s first year coincides with themaster’s programme. Ph.D. theses are pub-lished in the Institute’s Research Series.
For information on admission require-ments, application procedure, and scholar-ships, visit http://www.tinbergen.nl, or contact [email protected].
BoardA.G.Z. Kemna (Chair), J.S. Cramer,
S. Goyal, J. Hartog, P. Rietveld
General DirectorC.N. Teulings
Director of Graduate StudiesM. Lindeboom
Research Programme Co-ordinatorsInstitutions and Decision Analysis:
M.C.W. Janssen, F.A.A.M. van WindenFinancial Economics andInternational Markets:
C.G. de Vries, E.C. PerottiLabour, Region and the Environment:
Chair), M. Dewatripont (CORE), P. de Grauwe(Leuven University), D.F. Hendry (OxfordUniversity), R.C. Merton (Harvard University),D. Mortensen (Northwestern University), S. Nickell (Oxford University), T. Persson(Stockholm University), L. Wolsey (CORE)
Social Advisory CouncilC.A.J. Herkströter (Chair), R.G.C. van
den Brink (ABN-AMRO), H.J. Brouwer (DNB),M.J. Cohen (Mayor of Amsterdam),F.J.H. Don (CPB), C. Maas (ING), F.A. Maljers, I.W. Opstelten (Mayor of Rotterdam), A.H.G. Rinnooy Kan (ING), H. Schreuder(DSM), J. Stekelenburg, R.J. in ’t Veld, P.J. Vinken, L.J. de Waal (FNV)
How to subscribe?Address for correspondence/subscriptions:
Tinbergen Institute Rotterdam, Burg. Oudlaan 50, 3062 PA Rotterdam, The Netherlands. E-mail: [email protected] changes may be sent to the above e-mail address.
In this issue Economic Dynamics
From a linear, perfectly rational view towards bounded rationality,
non-linearity and complex adaptive systems
Global challenges of capital markets integration
Modern economics in action in poor countries
An interview with development economist Jan Willem Gunning
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